Occupancy sensors are designed to save energy by detecting the presence of a moving object in an area of coverage and switching a load (e.g., a light source, an HVAC system, etc.) on and off depending upon the presence of the moving object. For example, when motion is detected within the area of coverage, the load is turned on. Alternatively, when motion is not detected within the area of coverage, thus indicating that the area of coverage is not occupied, the load is turned off after a predetermined period of time. Occupancy sensors thus facilitate electrical energy savings by automating the functions of, for example, a light switch.
Occupancy sensors using passive infrared detection (PIR) have been employed in a variety of indoor applications with much success. PIR occupancy sensors operate by sensing a body having a heat signature in excess of background infrared (IR) levels. Since PIR occupancy sensors rely on body heat detection, indoor applications that experience limited temperature extremes are a near perfect environment, and the indoor PIR occupancy sensor can be easily tuned and tailored to identify body heat from the ambient temperature environment.
Although PIR occupancy sensors have also been used in outdoor applications, the ability to accurately detect the temperature produced by a human body or an automobile within a wide range of ambient temperatures is made more difficult. One reason for this, is because as the ambient temperature of a monitored area rises, the difference between human body temperature and the ambient temperature decreases, and as a result PIR occupancy sensors can be less able to differentiate the heat signature of a human body from the background heat signature of the surroundings. In addition, detection problems increase when road or parking surface temperatures rise, making it even more difficult for the PIR occupancy sensor to discern the heat signature of a moving object from the background heat signature of the road or parking surface.
Prior occupancy sensing systems also suffer from deficiencies in that they do not adequately take into account time of day. More particularly, prior outdoor occupancy sensing systems have thus far not had the capability to customize operation based on time of day so as to provide optimum energy savings during periods when low activity is expected.